1. Field of the Invention
The present invention relates generally to Ethernet networks and, more particularly, to a system and method for adjusting compression for computing clients based on a latency level.
2. Introduction
Client-server applications typically involve numerous tradeoffs regarding the various levels of processing to be performed on the client and the server. This decision can greatly influence the relative cost of the clients and servers.
One type of client is a thin client. A thin client can be designed with relatively little processing power such that the bulk of the data processing occurs on the server. The thin client can therefore be designed to focus on conveying input and output between the user and the application. This framework can be used in a server-centric computing model. In contrast, a thick client can be designed with significant processing power. Here, the thick client can be responsible for much of the data processing, while the server is largely responsible for centralized storage and control.
In between the thin and thick client classifications there can exist various hybrid clients. These hybrid clients can exhibit both thin and thick client properties depending on the particular function of the client device. In many instances, a thin client can be turned into a “chubby” client through the inclusion of additional processing capacity for a particular application. For example, compression circuitry and software can be added to a thin client to transform it into a chubby client.
One area of application of such client computing devices is in the transmission of streaming audio/video (AV). As would be appreciated, this transmission can occur in various wide area network (WAN), metropolitan area network (MAN), and local area network (LAN) contexts.
Many AV streams (e.g., video conferencing) can represent latency-sensitive traffic. For this type of traffic, compression and decompression of the AV stream between the two endpoints can take up a large part of the latency budget, thereby compromising end-to-end delay targets. In some cases, endpoint devices can seek to minimize the level of compression to meet worst-case assumptions used to address the unpredictable nature of network performance. While this process increases the likelihood of meeting end-to-end delay targets, it is not based on actual network performance. What is needed therefore is a mechanism for managing such endpoint devices in their efficient use of available network end-to-end delay budgets.